With the development of medical imaging technologies, the application of medical imaging devices has been popularized. As a huge amount of information is contained in an image obtained using a medical imaging device, a specialized person such as a doctor needs to extract a plurality of voxels from a target region of the observed object, check the obtained data voxel by voxel and empirically determine, for example, whether or not there is a voxel which may have abnormality, based on the data. This approach which requires voxels to be operated one by one is incapable of rapidly and efficiently recognizing a voxel which is significantly changed when compared with a normal one and the degree of the change and may miss a voxel which is not expected to have abnormality. Further, as the determination is merely based on personal experience, the result may be inaccurate.
Therefore, a technology is desired by means of which a significantly changed voxel can be automatically recognized rapidly and accurately to find a part worthy of attention for a further examination. Moreover, it is also expected to track the condition of the same part of the same patient and compare the conditions using this technology.